THIS IS THE ULTIMATE GET STARTED FAST COURSE . Make no mistake data is the new gold. The amount of data being generated is exploding, those that can mine and analyze it for actionable decisions ARE WINNING . That is what you will learn in this course. We deploy a "Use Case" approach to not only give you a real world situation but show you step by step how to apply various Natural Language Processing methods or tools to extract the data you need for a fast accurate solution. NO SUBSCRIPTIONS, NO software to buy, just the tools provided to you in this course! Why Data Analysis: "Over 2.5 quintillion bytes of data are created every single day, and it’s only going to grow from there. Today, it’s estimated that 1.7MB of data will be created every second for every person on earth." TOP 10 Reasons YOU should learn Data Analysis: 1. Take this course to unlock opportunities you never knew about. 2. You already use Natural Language Processing (NLP) applications without even knowing it (Spell Checkers, Chatbots, Siri, Alexa, Resume sites, News aggregators) 3. The Banking industry uses NLP data analysis for various loan application processing. 4. Investors use NLP data analysis for financial statement insights. 5. Marketers use NLP data analysis for advertising/content optimization. 6. Healthcare insurers use NLP data analysis for faster claims processing. 7. Higher Education schools and institutes use NLP data analysis for plagiarism checking. 8. Brand managers use NLP to monitor customer feedback and mood towards certain brands. 9. Law Firms use NLP data analysis for contract auditing. 10. The Luxury industry uses NLP data analysis to provide better purchase recommendations. **** Can you afford NOT TO cash in on the future? * Add a new dimension to your Search Engine Optimization (With better keywords) *Get higher conversions from your sales scripts. (By understanding why ones perform and others do not) *Increase the accuracy of your opponent profile. (Isolate words and phrases used most) All of this falls under the Domain of Natural Language Processing. Natural Language Processing, or NLP for short, is broadly defined as the automatic manipulation of natural language, like speech and text, by software. But that doesn't even come close to what you can do with NLP and a variety of Data. You will become familiar with some basics in the Python programming language and in the end, you will have a portable (virtual machine) personal arsenal of tools to leverage across any number of text data sources. Giving you and or your organization the edge now and moving forward. *Get the upper hand in Content Generation. (Optimized Content based on Analysis) As an organizational leader, If you wanted to generate insights for text data, this course is for you. If you are involved in Market research this course is for you. If you conduct any form of competitive analysis this course is for you. Political campaign strategists needing a deeper understanding of the opponent, you guessed it. THIS COURSE IS FOR YOU! *Level-Up in your Career with NOW SKILLS! (Instantly ADD MORE VALUE) What you will learn are HIGHLY transferable skills applicable across a wide range of industries beyond I.T. (Healthcare, Legal, Insurance, Politics and Business). Whether you are changing careers, a student, an MBA or in a leadership position; your analysis skills will improve tremendously! Are there other uses for what you learn? ABSOLUTELY . One example that was sent to me, was from a songwriter. Yes, you read that correctly, a songwriter using data analysis! This individual compiled a collection of the lyrics of the top selling songs in his genre for the past 10 years. Using the Token frequency and TF-IDF scripts to isolate most used and highest weighted words across all lyrics in an effort to write songs with an increased probability for success. OF_NOTE: He did acknowledge that were more factors that play into this, but he was determined to capture every advantage possible. "To be able to do data analysis like this by myself, gives me a broader range of thought and creativity as to what is possible for my music" C.H. As a BONUS you will be provided a product or service recommendation script! **** Unlike any other course I am aware of, YOU get a data analysis Virtual Machine ready to run out of the box! ****

Please note that, We have divided the "Econometrics" course in to TWO parts as follows: Econometrics#1:  Regression Modeling, Statistics with EViews Econometrics#2: Econometrics Modeling and Analysis in EViews This is the Second part and will cover Multivariate Modeling, Autocorrelation Techniques, VAR Modeling, Stationarity and Unit Root Testing, CoIntegration Testing and Volatility & ARCH Modeling. This course aims to provide basic to intermediate skills on implementing Econometrics/Predictive modelling concepts using Eviews software. Whilst its important to develop understanding of econometrics/quantitative modelling concepts, its equally important to be able to implement it using suitable software packages. This course fills the gap between understanding the concepts and implementing them practically. The course works across multiple software packages such as Eviews, MS Office, PDF writers, and Paint. Econometric modeling course aims to provide quantitative/econometric modelling skills typically/specifically in Finance sector. Quantitative methods and predictive modelling concepts could be extensively used in understanding the financial markets movements, and studying tests and effects. The course picks theoretical and practical datasets for econometrics/quantitative/predictive analysis. Implementations are done using Eviews software. Observations, interpretations, predictions and conclusions are explained then and there on the examples as we proceed through the training. The course also emphasizes on the regression models, and AIMS to also cover Auto-Correlation, Co-Integration and ARCH (Auto Regressive Conditional Heteroscedasticity) models.  Essential skillsets – Prior knowledge of Quantitative methods and MS Office, Paint  Desired skillsets — Understanding of Data Analysis and VBA toolpack in MS Excel will be useful The course works across multiple software packages such as Eviews, MS Office, PDF writers, and Paint.

Don't want to use Excel to present dashboards to your team ? No problem, use Qlik Sense instead ! From my experience many users just get hung up trying to tease Excel into creating data visualisations from the underlying spreadsheet data. This becomes a real issue when more than one workbook contains the required data for presentation, it quickly becomes a nightmare! What's the alternative ? Qlik Sense of course ! Qlik Sense is easy & intuitive to work with, simple drag and drop wizards. This course is presented from a user perspective making it very easy to present insight to an audience with confidence. You will get to ... Import data for instant insight Creating data visualisations and dashboards Conditional testing logic A Project assignment for you to test yourself with Data story creation User Experience enhancements Real world data for download At the end of the course you'll wonder why you ever struggled with Excel to build your data visualisations. Unleash your creative urges with Qlik Sense and impress your audience(s) Looking forward to seeing you in the course. Paul Data Analyst and Visualisation Engineer

Data analysis becomes essential part of every day life. After this course, you will be able to conduct data analysis task yourself. Gain insights from the data. Will be using R - widely used tool for data analysis and visualization. Data Science project will be core course component - will be working on it after mastering all necessary background. Doing data analysis from ground up to final insights. Starting from very basics we will move to various input and output methods. Yet another important concept - visualization capabilities. After the course you will be able to produce convincing graphs. Background behind functional programming will be presented - including building your own functions. After finishing the course you will feel much more comfortable programming in other languages as well. This is because R being fully empowered programming language itself. Main programming concepts presented: Various data types Conditional statements For and While loops No previous programming knowledge required. Finally, data mining and data science techniques in R delivered in clear fashion together with assignments to make sure you understand topics. Main statistical capabilities behind data science covered. Course is interactive . Specific topic covered in each lecture. Each lecture includes multiple examples. All material covered in videos are available for download! This way student is able to program himself - break things and fix them. Students will finish course in approximately 7-10 days working 3 hours per day. Time spent working individually included. After each section assignment should be completed to make sure you understand material in the section. After you are ready with the solution - watch video explaining concepts behind assignment. I will be ready to give you a hand by answering your questions. Finally, this course is specifically designed to get up to speed fast. Biggest emphasis put on real examples and programming yourself. This distinguishes this course from other material available online - usual courses includes vague slides and long textbooks with no real practise.

Everyone is talking about big data and GIS, but is anyone really doing it? In this course you’ll work with gigabytes of data to solve many different spatial and data related questions . All the software is free, but don't let that fool you: we'll be using the most effective open source products like Postgres and QGIS, and we'll even perform parallel processing with Manifold Viewer - I hope you have a multi-core computer to see how fast this stuff is! At the end of the course, you’ll understand: the principles behind big data geo-analytics and the role of statistics, databases, parallel processing, and hardware and software in support of big data geo-analytics. how to use open source software and Manifold GIS to perform parallel processing and manage spatial data. how to conduct a big data geo-analytics project by interrogating multi-gigabyte real world databases. And best of all, the software we use in this class is FREE and easy to set up - you'll do it all yourself! The course is taught by Dr. Arthur Lembo who is a Professor at Salisbury University and has worked in the GIS field for  over 30 years.

Student Testimonials: The instructor knows the material, and has detailed explanation on every topic he discusses. Has clarity too, and warns students of potential pitfalls. He has a very logical explanation, and it is easy to follow him. I highly recommend this class, and would look into taking a new class from him. - Diana This is excellent, and I cannot complement the instructor enough. Extremely clear, relevant, and high quality - with helpful practical tips and advice. Would recommend this to anyone wanting to learn pandas. Lessons are well constructed. I'm actually surprised at how well done this is. I don't give many 5 stars, but this has earned it so far. - Michael This course is very thorough, clear, and well thought out. This is the best Udemy course I have taken thus far. (This is my third course.) The instruction is excellent! - James Welcome to the most comprehensive Pandas course available on Udemy! An excellent choice for both beginners and experts looking to expand their knowledge on one of the most popular Python libraries in the world! Data Analysis with Pandas and Python offers 19+ hours of in-depth video tutorials on the most powerful data analysis toolkit available today. Lessons include: installing sorting filtering grouping aggregating de-duplicating pivoting munging deleting merging visualizing and more! Why learn pandas? If you've spent time in a spreadsheet software like Microsoft Excel, Apple Numbers, or Google Sheets and are eager to take your data analysis skills to the next level, this course is for you! Data Analysis with Pandas and Python introduces you to the popular Pandas library built on top of the Python programming language. Pandas is a powerhouse tool that allows you to do anything and everything with colossal data sets -- analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleaning, calculating, and more! I call it "Excel on steroids"! Over the course of more than 19 hours, I'll take you step-by-step through Pandas, from installation to visualization! We'll cover hundreds of different methods, attributes, features, and functionalities packed away inside this awesome library. We'll dive into tons of different datasets, short and long, broken and pristine, to demonstrate the incredible versatility and efficiency of this package. Data Analysis with Pandas and Python is bundled with dozens of datasets for you to use. Dive right in and follow along with my lessons to see how easy it is to get started with pandas! Whether you're a new data analyst or have spent years (*cough* too long *cough*) in Excel, Data Analysis with pandas and Python offers you an incredible introduction to one of the most powerful data toolkits available today!

Learn how to define a Pentaho Kafka Producer and Consumer to implement a quick solution to derive insights. This course is accompanied with a demo project related to banking domain and as a student of this course, you will get practical application of how Apache Kafka and Pentaho can be used in implementing a real time data streaming solution to discover the market demand for loan or total page visit count in real time. Content and Overview Through this course, comprising of several lectures with English subtitles / English captions, Quiz chapters, along with additional resources, you will Understand what is, when and how to carry out realtime data processing solution Gain confidence in implementing such realtime data processing solution using Pentaho and Kafka You can test the knowledge gained through the sessions by attending quizzes and every use case mentioned in the course are explained with demo sessions thereby enabling you to practice the newly learned skills. I will add more contents to this course as and when possible. Downloadable Resources You can download the Pentaho transformations used during the demo sessions (attached as part of a resource material in a lecture of this course), to practice at your end. Learners who complete this course will gain the knowledge and confidence to implement a realtime data streaming solution with Pentaho and Apache Kafka in the projects.

The Problem Data scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace. However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist. And how can you do that? Universities have been slow at creating specialized data science programs. (not to mention that the ones that exist are very expensive and time consuming) Most online courses focus on a specific topic and it is difficult to understand how the skill they teach fit in the complete picture The Solution Data science is a multidisciplinary field. It encompasses a wide range of topics. Understanding of the data science field and the type of analysis carried out Mathematics Statistics Python Applying advanced statistical techniques in Python Data Visualization Machine Learning Deep Learning Each of these topics builds on the previous ones. And you risk getting lost along the way if you don’t acquire these skills in the right order. For example, one would struggle in the application of Machine Learning techniques before understanding the underlying Mathematics. Or, it can be overwhelming to study regression analysis in Python before knowing what a regression is. So, in an effort to create the most effective, time-efficient, and structured data science training available online, we created The Data Science Course 2021. We believe this is the first training program that solves the biggest challenge to entering the data science field – having all the necessary resources in one place. Moreover, our focus is to teach topics that flow smoothly and complement each other. The course teaches you everything you need to know to become a data scientist at a fraction of the cost of traditional programs (not to mention the amount of time you will save). The Skills 1. Intro to Data and Data Science Big data, business intelligence, business analytics, machine learning and artificial intelligence. We know these buzzwords belong to the field of data science but what do they all mean? Why learn it? As a candidate data scientist, you must understand the ins and outs of each of these areas and recognise the appropriate approach to solving a problem. This ‘Intro to data and data science’ will give you a comprehensive look at all these buzzwords and where they fit in the realm of data science. 2. Mathematics Learning the tools is the first step to doing data science. You must first see the big picture to then examine the parts in detail. We take a detailed look specifically at calculus and linear algebra as they are the subfields data science relies on. Why learn it? Calculus and linear algebra are essential for programming in data science. If you want to understand advanced machine learning algorithms, then you need these skills in your arsenal. 3. Statistics You need to think like a scientist before you can become a scientist. Statistics trains your mind to frame problems as hypotheses and gives you techniques to test these hypotheses, just like a scientist. Why learn it? This course doesn’t just give you the tools you need but teaches you how to use them. Statistics trains you to think like a scientist. 4. Python Python is a relatively new programming language and, unlike R, it is a general-purpose programming language. You can do anything with it! Web applications, computer games and data science are among many of its capabilities. That’s why, in a short space of time, it has managed to disrupt many disciplines. Extremely powerful libraries have been developed to enable data manipulation, transformation, and visualisation. Where Python really shines however, is when it deals with machine and deep learning. Why learn it? When it comes to developing, implementing, and deploying machine learning models through powerful frameworks such as scikit-learn, TensorFlow, etc, Python is a must have programming language. 5. Tableau Data scientists don’t just need to deal with data and solve data driven problems. They also need to convince company executives of the right decisions to make. These executives may not be well versed in data science, so the data scientist must but be able to present and visualise the data’s story in a way they will understand. That’s where Tableau comes in – and we will help you become an expert story teller using the leading visualisation software in business intelligence and data science. Why learn it? A data scientist relies on business intelligence tools like Tableau to communicate complex results to non-technical decision makers. 6. Advanced Statistics Regressions, clustering, and factor analysis are all disciplines that were invented before machine learning. However, now these statistical methods are all performed through machine learning to provide predictions with unparalleled accuracy. This section will look at these techniques in detail. Why learn it? Data science is all about predictive modelling and you can become an expert in these methods through this ‘advance statistics’ section. 7. Machine Learning The final part of the program and what every section has been leading up to is deep learning. Being able to employ machine and deep learning in their work is what often separates a data scientist from a data analyst. This section covers all common machine learning techniques and deep learning methods with TensorFlow. Why learn it? Machine learning is everywhere. Companies like Facebook, Google, and Amazon have been using machines that can learn on their own for years. Now is the time for you to control the machines. ***What you get*** A $1250 data science training program Active Q&A support All the knowledge to get hired as a data scientist A community of data science learners A certificate of completion Access to future updates Solve real-life business cases that will get you the job You will become a data scientist from scratch We are happy to offer an unconditional 30-day money back in full guarantee. No risk for you. The content of the course is excellent, and this is a no-brainer for us, as we are certain you will love it. Why wait? Every day is a missed opportunity. Click the “Buy Now” button and become a part of our data scientist program today.

PLEASE READ BEFORE ENROLLING: 1.) THERE IS AN UPDATED VERSION OF THIS COURSE: "PYTHON FOR DATA SCIENCE AND MACHINE LEARNING BOOTCAMP" 2.) IF YOU ARE A COMPLETE BEGINNER IN PYTHON-CHECK OUT MY OTHER COURSE "COMPLETE PYTHON MASTERCLASS JOURNEY"! CLICK ON MY PROFILE TO FIND IT. (PLEASE WATCH THE FIRST PROMO VIDEO ON THIS PAGE FOR MORE INFO) ********************************************************************************************************** This course will give you the resources to learn python and effectively use it analyze and visualize data! Start your career in Data Science! You'll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyze data. You will also get lifetime access to over 100 example python code notebooks, new and updated videos, as well as future additions of various data analysis projects that you can use for a portfolio to show future employers! By the end of this course you will: - Have an understanding of how to program in Python. - Know how to create and manipulate arrays using numpy and Python. - Know how to use pandas to create and analyze data sets. - Know how to use matplotlib and seaborn libraries to create beautiful data visualization. - Have an amazing portfolio of example python data analysis projects! - Have an understanding of Machine Learning and SciKit Learn! With 100+ lectures and over 20 hours of information and more than 100 example python code notebooks, you will be excellently prepared for a future in data science!

This is an introductory course designed to help business professionals and others learn predictive analytic skills that can be applied in a business setting. Since it is designed for business professionals it doesn't delve too deeply into the mathematics of the statistical models. We do the following case studies on Rapidminer software: B2B Churn of an office supply distributor, Market Basket Analysis of a retail computer store, Customer Segmentation of a customer database and Direct Marketing. The following models are used: Linear Regression, Logistic Regression, Association Rules, K-means Clustering and Decision Trees. Through these practical case studies we generate actionable business insights!